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DBMS > Databricks vs. LeanXcale vs. Oracle Berkeley DB

System Properties Comparison Databricks vs. LeanXcale vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLeanXcale  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesWidely used in-process key-value store
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitewww.databricks.comwww.leanxcale.comwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationdocs.databricks.comdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperDatabricksLeanXcaleOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release201320151994
Current release18.1.40, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyes
SQL infoSupport of SQLwith Databricks SQLyes infothrough Apache Derbyyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languagesPython
R
Scala
C
Java
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesno
Triggersyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlno
More information provided by the system vendor
DatabricksLeanXcaleOracle Berkeley DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLeanXcaleOracle Berkeley DB
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